Abstract
We consider the linear regression model where only a particular linear function of the dependent variables is observed, Stahlecker and Schmidt (1987) proposed a “naive” least squares (LS) estimator for regression coefficients in such a case. In this note we represent their estimator as a general ridge estimator. This observation leads to a view different from the previous work and provides an easy way of obtaining many important properties of the naive LS estimator. Our approach also gives some insight into the relationship between the naive LS estimator and the generalized least squares estimator.
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Liski, E.P., Wang, SG. Another look at the naive estimator in a regression model. Metrika 41, 55–64 (1994). https://doi.org/10.1007/BF01895304
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DOI: https://doi.org/10.1007/BF01895304